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make style

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This commit is contained in:
Patrick von Platen
2023-01-27 16:52:04 +02:00
parent 31be42209d
commit 97ef5e0665
8 changed files with 15 additions and 34 deletions
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5
examples/research_projects/intel_opts/textual_inversion/textual_inversion_bf16.py
View File

@@ -336,10 +336,7 @@ class TextualInversionDataset(Dataset):
if self.center_crop:
crop = min(img.shape[0], img.shape[1])
(
h,
w,
) = (
(h, w,) = (
img.shape[0],
img.shape[1],
)

5
examples/textual_inversion/textual_inversion.py
View File

@@ -432,10 +432,7 @@ class TextualInversionDataset(Dataset):
if self.center_crop:
crop = min(img.shape[0], img.shape[1])
(
h,
w,
) = (
(h, w,) = (
img.shape[0],
img.shape[1],
)

5
examples/textual_inversion/textual_inversion_flax.py
View File

@@ -306,10 +306,7 @@ class TextualInversionDataset(Dataset):
if self.center_crop:
crop = min(img.shape[0], img.shape[1])
(
h,
w,
) = (
(h, w,) = (
img.shape[0],
img.shape[1],
)

6
src/diffusers/models/attention.py
View File

@@ -94,10 +94,8 @@ class AttentionBlock(nn.Module):
if use_memory_efficient_attention_xformers:
if not is_xformers_available():
raise ModuleNotFoundError(
(
"Refer to https://github.com/facebookresearch/xformers for more information on how to install"
" xformers"
),
"Refer to https://github.com/facebookresearch/xformers for more information on how to install"
" xformers",
name="xformers",
)
elif not torch.cuda.is_available():

6
src/diffusers/models/cross_attention.py
View File

@@ -111,10 +111,8 @@ class CrossAttention(nn.Module):
)
elif not is_xformers_available():
raise ModuleNotFoundError(
(
"Refer to https://github.com/facebookresearch/xformers for more information on how to install"
" xformers"
),
"Refer to https://github.com/facebookresearch/xformers for more information on how to install"
" xformers",
name="xformers",
)
elif not torch.cuda.is_available():

8
src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py
View File

@@ -189,11 +189,9 @@ class EulerAncestralDiscreteScheduler(SchedulerMixin, ConfigMixin):
or isinstance(timestep, torch.LongTensor)
):
raise ValueError(
(
"Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
" `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
" one of the `scheduler.timesteps` as a timestep."
),
"Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
" `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
" one of the `scheduler.timesteps` as a timestep.",
)
if not self.is_scale_input_called:

8
src/diffusers/schedulers/scheduling_euler_discrete.py
View File

@@ -198,11 +198,9 @@ class EulerDiscreteScheduler(SchedulerMixin, ConfigMixin):
or isinstance(timestep, torch.LongTensor)
):
raise ValueError(
(
"Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
" `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
" one of the `scheduler.timesteps` as a timestep."
),
"Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
" `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
" one of the `scheduler.timesteps` as a timestep.",
)
if not self.is_scale_input_called:

6
tests/test_scheduler.py
View File

@@ -537,10 +537,8 @@ class SchedulerCommonTest(unittest.TestCase):
)
self.assertTrue(
hasattr(scheduler, "scale_model_input"),
(
f"{scheduler_class} does not implement a required class method `scale_model_input(sample,"
" timestep)`"
),
f"{scheduler_class} does not implement a required class method `scale_model_input(sample,"
" timestep)`",
)
self.assertTrue(
hasattr(scheduler, "step"),